Federated Learning

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Overview

Federated learning studies how multiple devices or institutions can train models collaboratively while keeping data local, for example across hospitals, phones, or companies. A common approach, FedAvg, aggregates local model updates; related methods use personalization or client clustering, split learning, model compression, and lightweight adapters such as LoRA. Differential privacy and secure aggregation can limit exposure of updates, while robust aggregation and client-selection methods address malicious participants and uneven data or resources. The central challenge is balancing accuracy and fairness across heterogeneous clients with privacy, security, communication cost, and reliable evaluation; keeping data local alone does not guarantee privacy or strong performance.

Latest papers

CardsList

961 papers112 papers in the last four weeks, up 1% on the four weeks before. 0.6% of all new papers.

  1. Federated Learning of Binary Neural Networks: Enabling Low-Cost Inference

    Mar 16, 2026Nitin Priyadarshini Shankar, Soham Lahiri, Sheetal Kalyani +1Binary Neural NetworksFederated Learning

    Department of Electrical Engineering, Indian Institute of Technology Madras · Department of Computer Science and Engineering, Jadavpur University

  2. Joint Routing and Model Pruning for Decentralized Federated Learning in Bandwidth-Constrained Multi-Hop Wireless Networks

    Mar 16, 2026Xiaoyu He, Weicai Li, Tiejun Lv +1Federated LearningCommunication-Efficient Distributed Training

    School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China · Center for Target Cognition Information Processing Science and Technology, and the Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, both at Beijing Information Science and Technology University, Beijing, China

  3. SFedHIFI: Fire Rate-Based Heterogeneous Information Fusion for Spiking Federated Learning

    Mar 16, 2026Ran Tao, Qiugang Zhan, Shantian Yang +3Federated LearningHeterogeneous Federated Learning

    Complex Laboratory of New Finance and Economics, School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, China · Engineering Research Center of Intelligent Finance, Ministry of Education, China · Kash Institute of Electronics and Information Industry, China +2

  4. Personalized Federated Learning with Residual Fisher Information for Medical Image Segmentation

    Mar 16, 2026Meilu Zhu, Yuxing Li, Zhiwei Wang +1Federated LearningHeterogeneous Federated Learning

    Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China

  5. HO-SFL: Hybrid-Order Split Federated Learning with Backprop-Free Clients and Dimension-Free Aggregation

    Mar 16, 2026Qiyuan Chen, Xian Wu, Yi Wang +1Communication-Efficient Distributed TrainingZeroth-Order Optimization

    Department of Electrical and Computer Engineering, The University of Hong Kong, Hong Kong SAR, China.

  6. Domain-Skewed Federated Learning with Feature Decoupling and Calibration

    Mar 15, 2026Huan Wang, Jun Shen, Jun Yan +1Federated LearningHeterogeneous Federated Learning

    School of Computing and Information Technology, University of Wollongong, Australia · School of Computing and Information Systems, Singapore Management University, Singapore

  7. Efficient Federated Conformal Prediction with Group-Conditional Guarantee

    Mar 15, 2026Haifeng Wen, Osvaldo Simeone, Hong XingFederated Conformal PredictionGroup-Conditional Conformal Prediction

    1IoT Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · Institute for Intelligent Networked Systems (INSI), Northeastern University London, London, UK · Department of ECE, The Hong Kong University of Science and Technology, HK SAR

  8. MLFCIL: A Multi-Level Forgetting Mitigation Framework for Federated Class-Incremental Learning in LEO Satellites

    Mar 14, 2026Heng Zhang, Xiaohong Deng, Sijing Duan +4Remote Sensing Scene ClassificationFederated Continual Learning

    School of Information Engineering, Gannan University of Science and Technology, Ganzhou 341000, China · Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China · Department of Electrical and Computer Engineering, Queen University, Kingston, ON K7L 3N6, Canada +2

  9. FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for Non-IID Data

    Mar 14, 2026Eman M. AbouNassar, Amr Elshall, Sameh AbdulahFederated LearningNon-IID Federated Learning

    Mathematics and Computer Science Department, Faculty of Science, Menoufia University, Shebin El Koom, Egypt. · Computer Science Department, Faculty of Computers and Information, Menoufia University, Shebin El Koom, Egypt.

  10. DPxFin: Adaptive Differential Privacy for Anti-Money Laundering Detection via Reputation-Weighted Federated Learning

    Mar 14, 2026Renuga Kanagavelu, Manjil Nepal, Ning Peiyan +6Anti-Money Laundering DetectionDifferentially Private Federated Learning

    A*STAR IHPC Singapore · SRM University-AP Andhra Pradesh, India · EVYD Singapore

  11. Computation and Communication Efficient Federated Unlearning via On-server Gradient Conflict Mitigation and Expression

    Mar 14, 2026Minh-Duong Nguyen, Senura Hansaja, Le-Tuan Nguyen +4Federated UnlearningFederated Learning

    VinUniversity · University of Sydney · Trinity College Dublin

  12. Privacy-Preserving Machine Learning for IoT: A Cross-Paradigm Survey and Future Roadmap

    Mar 13, 2026Zakia Zaman, Praveen Gauravaram, Mahbub Hassan +2Privacy-Preserving MLInternet of Things

    School of CSE, University of NSW, AU · TCS Research & Innovation, Tata Consultancy Services (Australia & New Zealand), Australia

  13. Federated Few-Shot Learning on Neuromorphic Hardware: An Empirical Study Across Physical Edge Nodes

    Mar 13, 2026Steven Motta, Gioele NanniFederated LearningFederated Learning Aggregation

  14. SCOPE: Scalable Training-Free Semantic Coreset Selection for Long-Tailed Federated Learning

    Mar 13, 2026Md Anwar Hossen, Nathan R. Tallent, Luanzheng Guo +1Federated LearningCommunication-Efficient Distributed Training

    Iowa State University, Ames, Iowa, USA · Pacific Northwest National Laboratory, Richland, WA, USA

  15. FedBPrompt: Federated Domain Generalization Person Re-Identification via Body Distribution Aware Visual Prompts

    Mar 13, 2026Xin Xu, Weilong Li, Wei Liu +5Federated Domain GeneralizationPerson Re-Identification

    School of Computer Science and Technology, Wuhan University of Science and Technology, China · Nanyang Technological University, Singapore · NERC for Multimedia Software, School of Computer Science, Wuhan University, China +3

  16. CA-HFP: Curvature-Aware Heterogeneous Federated Pruning with Model Reconstruction

    Mar 13, 2026Gang Hu, Yinglei Teng, Pengfei Wu +1Federated LearningHeterogeneous Federated Learning

  17. Projection Guided Personalized Federated Learning for Low Dose CT Denoising

    Mar 12, 2026Anas Zafar, Muhammad Waqas, Amgad Muneer +2LDCT DenoisingFederated Learning

    The University of Texas MD Anderson Cancer Center, Houston, TX, USA

  18. Decentralized Orchestration Architecture for Fluid Computing: A Secure Distributed AI Use Case

    Mar 12, 2026Diego Cajaraville-Aboy, Ana Fernández-Vilas, Rebeca P. Díaz-Redondo +2Byzantine-Robust Federated LearningEdge-Cloud Computing

    atlanTTic Research Center – ICLAB – Universidade de Vigo, Vigo, 36310, Spain

  19. Few-for-Many Personalized Federated Learning

    Mar 12, 2026Ping Guo, Tiantian Zhang, Xi Lin +3Federated LearningHeterogeneous Federated Learning

    City University of Hong Kong · CityU Shenzhen Research Institute · Hong Kong Metropolitan University +3

  20. Deep Learning-based Assessment of the Relation Between the Third Molar and Mandibular Canal on Panoramic Radiographs using Local, Centralized, and Federated Learning

    Mar 12, 2026Johan Andreas Balle Rubak, Sara Haghighat, Sanyam Jain +9Medical Image ClassificationMedical Imaging

    Department of Dentistry and Oral Health, Aarhus University, Vennelyst Boulevard 9, Aarhus, 8000, Denmark · Private Dental Practice Dr. Jörg Deike, Hannover, Germany · Department of Oral Medicine and Radiology, King George's Medical University, India. Shah Mina Road, Chowk, Lucknow, Uttar Pradesh 226003, India +6

  21. FL-MedSegBench: A Comprehensive Benchmark for Federated Learning on Medical Image Segmentation

    Mar 12, 2026Meilu Zhu, Zhiwei Wang, Axiu Mao +4Federated LearningMedical Image Benchmarks

    Department of Electrical and Computer Engineering, The University of Hong Kong, Hong Kong, China · School of Communication Engineering, Hangzhou Dianzi University, Hang Zhou, China · Department of Radiation Oncology, Stanford University, California, USA +1

  22. Personalized Federated Learning via Gaussian Generative Modeling

    Mar 12, 2026Peng Hu, Jianwei MaFederated LearningHeterogeneous Federated Learning

    P. Hu is with the School of Mathematics, Harbin Institute of Technology, Harbin, China. · J. Ma is with the Institute for Artificial Intelligence and the School of Earth and Space Sciences, Peking University, Beijing, China, and also with the Institute for Artificial Intelligence and the School of Mathematics, Harbin Institute of Technology, Harbin, China.

  23. FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources

    Mar 11, 2026Md Sirajul Islam, Isabelle G Chapman, N I Md Ashafuddula +4Online Federated LearningFederated Learning

    School of Computing and Informatics, University of Louisiana at Lafayette, USA · Department of Computer and Information Sciences, University of Delaware, USA · Department of Computer Science, University of Illinois at Urbana-Champaign, USA

  24. Client-Conditional Federated Learning via Local Training Data Statistics

    Mar 11, 2026Rickard BrännvallFederated LearningNon-IID Federated Learning

    RISE Research Institutes of Sweden

  25. Federated Learning-driven Beam Management in LEO 6G Non-Terrestrial Networks

    Mar 11, 2026Maria Lamprini Bartsioka, Ioannis A. Bartsiokas, Athanasios D. Panagopoulos +2LEO Satellite Networks6G Networks

  26. FRIEND: Federated Learning for Joint Optimization of multi-RIS Configuration and Eavesdropper Intelligent Detection in B5G Networks

    Mar 11, 2026Maria Lamprini A. Bartsioka, Ioannis A. Bartsiokas, Anastasios K. Papazafeiropoulos +3Industrial Internet of ThingsWireless Communications

    Microwave and Fiber Optics Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Heroon Polytechneiou str, Zografou 15780, Athens, Greece · Communications and Intelligent Systems Research Group, University of Hertfordshire, AL10 9AB Hatfield, U.K. · Intelligent Communications and Broadband Networks Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Heroon Polytechneiou str, Zografou 15780, Athens, Greece

  27. Med-DualLoRA: Local Adaptation of Foundation Models for 3D Cardiac MRI

    Mar 11, 2026Joan Perramon-Llussà, Amelia Jiménez-Sánchez, Grzegorz Skorupko +4Federated Fine-TuningMedical Imaging Foundation Models

    Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Spain · Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain

  28. Prioritizing Gradient Sign Over Modulus: An Importance-Aware Framework for Wireless Federated Learning

    Mar 11, 2026Yiyang Yue, Jiacheng Yao, Wei Xu +3Federated LearningCommunication-Efficient Distributed Training

    National Mobile Communications Research Laboratory (NCRL), Southeast University, Nanjing 210096, China · Purple Mountain Laboratories, Nanjing 211111, China · Zhejiang Lab, Hangzhou 311121, China +3

  29. Federated Active Learning Under Extreme Non-IID and Global Class Imbalance

    Mar 11, 2026Chen-Chen Zong, Sheng-Jun HuangActive LearningFederated Learning

    Nanjing University of Aeronautics and Astronautics, China

  30. A Multi-Prototype-Guided Federated Knowledge Distillation Approach in AI-RAN Enabled Multi-Access Edge Computing System

    Mar 10, 2026Luyao Zou, Hayoung Oh, Chu Myaet Thwal +3Federated Knowledge DistillationFederated Learning

    College of Computing and Informatics, Sungkyunkwan University, Republic of Korea · Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, 17104, Republic of Korea · Department of Information and Communication Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh +2